Senior Staff Machine Learning Engineer, (ML Underwriting) Job at Affirm in San J

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Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

Join the team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to affirms mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques to ensure responsible and accessible financial products.

In this role, you will help shape the future of machine learning at affirm. Youll partner with ML Platform, engineering, product, and risk leaders to design, implement, and scale advanced modeling approaches that drive critical decisions across the company. You will elevate our modeling capabilities, influence architectural direction, and ensure our systems can support increasingly sophisticated workloads. You will mentor senior engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long?term ML strategy. If you are passionate about modern machine learning and excited to drive high?impact innovation across a growing organization, affirm is the place for you.

What Youll Do

• You will define and drive multi?year, multi?team technical strategy for machine learning across affirm, ensuring alignment with company?wide priorities and influencing the roadmaps of partner teams and platforms.
• You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross?functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads.
• You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long?term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next?generation ML methods.
• You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross?org guidance.
• You will drive clarity and alignment on ambiguous, high?stakes technical decisions, resolving cross?team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization.
• You will champion operational and system excellence at the area level, owning the long?term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams.

What We Look For

• You have 10+ years of experience researching, designing, deploying, and operating large?scale, real?time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE.
• You have experience leading end?to?end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. You use distributed frameworks such as Spark, Ray, or similar large?scale data processing systems.
• You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
• You have a strong understanding of representation learning and embedding?based modeling. You possess deep expertise in neural network?based sequence modeling, including architectures such as Transformers, recurrent, or attention?based models, and multi?task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
• You have deep hands?on experience with large?scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining.
• You provide strong technical leadership: defining long?term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
• You demonstrate exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
• You have strong verbal and written communication skills that support effective collaboration across our global engineering organization.
• This position requires equivalent practical experience or a Bachelors degree in a related field.

Pay Grade - R

Equity Grade - 15

Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job?related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000

USA base pay range (all other U.S. states) per year: $232,000 - $282,000

Remote
Affirm is proud to be a remote?first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned affirm office. A limited number of roles remain office?based due to the nature of their job responsibilities.

Benefits

Were extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

• Health care coverage affirm covers all premiums for all levels of coverage for you and your dependents
• Flexible Spending Wallets generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
• Time off competitive vacation and holiday schedules allowing you to take time off to rest and recharge
• ESPP An employee stock purchase plan enabling you to buy shares of affirm at a discount

We believe its On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, affirm will consider for employment qualified applicants with arrest and conviction records.

By clicking Submit Application, you acknowledge that you have read affirms Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

Seniority level

Mid?Senior level

Employment type

Full?time

Job function

Engineering and Information Technology

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In Summary: Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest . Join the team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team . We are utilizing advanced machine learning techniques to ensure responsible and accessible financial products .

En Español: Únase a unirse para solicitar el cargo de Ingeniero Senior Staff Machine Learning (ML Underwriting) en Affirm Afirm está reinventando el crédito para hacerlo más honesto y amigable, dándole a los consumidores la flexibilidad de comprar ahora y pagar después sin tarifas ocultas o intereses compuestos. Únete al equipo como ingeniero senior staff machine learning y conviértete en una parte fundamental de nuestro innovador equipo ML. Nuestro equipo se dedica a afirmar la misión de revolucionar los servicios financieros con transparencia e inclusión en su núcleo. Estamos utilizando técnicas de aprendizaje automático para garantizar productos financieros responsables y accesibles. Definirá y impulsará la estrategia técnica de aprendizaje automático multianual, multi-equipo para afirmar, asegurando una alineación con las prioridades de toda la empresa e influir en los mapas de ruta de equipos y plataformas asociadas. Dirigirá el diseño, implementación y escalado de sistemas avanzados de ML, establecerá la dirección arquitectónica para iniciativas complejas, interfuncionales y garantizar que los sistemas permanezcan fiables, extensibles y preparados para cargas de trabajo de modelado cada vez más sofisticadas. Se asociará profundamente con la plataforma, producto, ingeniería y liderazgo del riesgo para dar forma a las capacidades de modelización a largo plazo, definir nuevas oportunidades de impacto de ML y guiar la evolución de infraestructura requerida para métodos técnicos de próxima generación de ML. Proporcionará un amplio liderazco a través de la organización de pruebas técnicas de ML; garantizará la elevación del diseño y la calidad del código, y se aseguran que los procesos de gestión transversales sean conocimientos especializados, claridad y orientación técnica. Lo que buscamos Usted tiene más de 10 años de experiencia en la investigación, diseño, implementación y operación de sistemas de aprendizaje automático a gran escala en tiempo real con un historial comprobado de impulsar la innovación técnica y ofrecer un impacto comercial medible. El doctorado relevante puede contar hasta 2 YOE. Tiene experiencia en el diseño del sistema ML de extremo al extremo, desde la arquitectura de datos y las tuberías de características hasta el entrenamiento, evaluación y despliegue de modelos. Utiliza marcos distribuidos como Spark, Ray o sistemas similares de procesamiento de datos a grande escala. Conoce bien los marcos Python y ML, incluyendo PyTorch y XGBoost. Proporcionas un fuerte liderazgo técnico: definiendo una estrategia a largo plazo, guiando la dirección de la investigación y alineando el trabajo entre equipos. Eres reconocido como un experto confiable que puede impulsar la claridad y la ejecución incluso en espacios problemáticos ambiguos. Demostras juicio excepcional, colaboración y habilidades de comunicación, permitiendo discusiones técnicas efectivas con ingenieros, investigadores y ejecutivos. Consegues a los ingenieros superiores, fomentas la excelencia técnica y contribuyes a una cultura del aprendizaje continuo. Tienes fuertes habilidades verbales y escritas de comunicación que apoyan la colaboración efectiva en toda nuestra organización global de ingeniería. Esta posición requiere experiencia práctica equivalente o una licenciatura en un campo relacionado. Grado de pago - R Equidad - 15 Afirma se centra en proporcionar una estructura simple y salarial basada en una variedad de factores, incluida ubicación remota, experiencia laboral y aptitudes básicas. ¿La gama total de beneficios de compensación médica es parte de un paquete dependiente que puede cubrir casi $ 230.000 dólares por año? Los aseguradores en roles cercanos tienen la flexibilidad de trabajar remotamente, pero ocasionalmente se les pedirá que trabajen fuera de su oficina afirmativa asignada. Un número limitado de puestos permanecen basados en oficinas debido a la naturaleza de sus responsabilidades laborales. Beneficios Fuimos extremadamente orgullosos de ofrecer beneficios competitivos anclados en nuestro valor fundamental de las personas primero. Algunos puntos destacados clave de nuestro paquete de beneficios incluyen: La cobertura del cuidado de salud afirma cubre todas las primas para todos los niveles de cobertura para usted y sus dependientes Bolsas de gastos flexibles Becas generosas por gastar en Tecnología, Alimentos, diversas necesidades de estilo de vida y costumbres familiares Horario libre de vacaciones competitivas y horarios vacacionales que le permiten tomarse un tiempo libre para descansar y recar Registros del plan de empleado ESPP que le permite comprar descuento En Estados Unidos podemos proveer una entrevista con personas calificadas, incluyendo el Acceso a la Oficina de San Francisco o la Ordenanza de Asistencia Personales (ESP) creemos que los solicitantes de acceso al empleo pueden ser considerados como sujetos a condiciones razonables durante todo el proceso de arresto e Infraestructuración. Al hacer clic en Enviar solicitud, usted reconoce que ha leído la Declaración de privacidad global del candidato y por lo tanto da su consentimiento informado libremente e inequívocamente a la recopilación, procesamiento, uso y almacenamiento de su información personal como se describe en ella.